SITE SHIELD is an AI-powered video intelligence platform that analyzes live video in real time to detect safety risks, violations, and incidents.
Unlike traditional CCTV systems that only record footage, SITE SHIELD understands video, generates events, triggers alerts, and supports incident resolution automatically.

SITE SHIELD is built for environments where safety, security, and compliance are critical, including:

• Industrial & manufacturing plants

• Construction sites

• Warehouses & logistics hubs

• Campuses and retail spaces

• Railways, ports, and airports

SITE SHIELD is a core AI platform offered as multiple industry-specific product variants, each engineered to address the unique safety, security, and operational challenges of that industry.

Yes. SITE SHIELD is camera-agnostic and supports most IP and ONVIF-compliant cameras, including fixed, ANPR and PTZ cameras.
This allows organizations to leverage existing camera investments without large hardware replacement costs.

SITE SHIELD uses industry-specific AI models designed for real-world operating conditions. Accuracy is achieved through context-aware detection, confidence thresholds, and rule-based filtering, rather than raw AI predictions alone.

False alerts are managed through:

• Zone and rule configuration

• Adjustable confidence thresholds

• Environment-specific calibration during deployment

This ensures SITE SHIELD delivers highly relevant alerts with minimal noise, even in challenging environments such as low light, crowded scenes, or complex sites.

SITE SHIELD follows a security-first, privacy-by-design architecture, including:

• Role-based access control (RBAC)

• Encrypted data in transit and at rest

• Immutable audit logs

• Configurable data retention policies

This makes SITE SHIELD suitable for enterprise, critical infrastructure, and government deployments.

SITE SHIELD supports three flexible deployment models to meet different security, compliance, and operational requirements:

• On-Premise – AI processing and data remain within the customer’s infrastructure, ideal for regulated or high-security environments.

• Cloud – Centralized deployment for multi-site monitoring with scalable infrastructure and remote access.

• Hybrid – Combines edge or on-premise AI processing with centralized cloud dashboards and management.

Organizations can choose or evolve between deployment models based on policy, scale, and security needs.

When AI detects a risk or violation, SITE SHIELD:

• Generates a structured event

• Sends real-time alerts to the relevant teams

• Creates an incident with video evidence

• Tracks resolution through dashboards and audit logs

This ensures fast response, accountability, and traceability.

Organizations typically achieve ROI through:

• Reduction in safety incidents and near-misses

• Lower compliance and audit effort

• Reduced dependence on manual monitoring

• Improved operational uptime and asset protection

SITE SHIELD transforms safety and surveillance from a reactive cost center into a measurable operational advantage.

Automated traffic enforcement ensures consistent, unbiased, and continuous monitoring without reliance on physical manpower.
Unlike manual enforcement, it reduces selective enforcement, human error, and operational fatigue.
By increasing the certainty and visibility of enforcement rather than penalty severity, automated systems encourage sustained behavior change and measurable improvements in road safety outcomes.

AI-based video analytics can detect a wide range of movement-based and behavioral violations.
Common examples include speed violations, red light violations, wrong-way driving, stopped vehicles on live lanes, illegal U-turns, no helmet riding, and triple seat riding.
These systems are especially effective in mixed traffic conditions and provide visual evidence that improves transparency and legal defensibility.

Modern video-based traffic systems can achieve high accuracy when designed, calibrated, and validated correctly.
Accuracy depends on factors such as camera placement, lighting and weather conditions, algorithm performance, and validation workflows.
Mature systems treat accuracy and validation as governance requirements, supported by calibration routines, periodic audits, and structured evidence review processes.

Automated Traffic Counting and Classification (ATCC) systems continuously measure traffic volume, speed, and vehicle composition.
On highways, ATCC supports capacity analysis, pavement design, freight movement studies, and performance monitoring.
In urban environments, it supports corridor planning, intersection design, and policy evaluation.
ATCC provides reliable long-term data that forms the foundation for evidence-based traffic planning and investment decisions.

An Integrated Command and Control Center (ICCC) acts as the centralized coordination hub for traffic operations, enforcement, and emergency response.
It aggregates real-time traffic data, incidents, violations, and video feeds into a unified operational view.
During emergencies, the ICCC enables coordination between traffic police, ambulance, fire, and city authorities, supporting faster response, safer access routes, and effective incident management.

Traffic Management Systems integrate with Smart City platforms through secure APIs, data feeds, and event-based messaging.
They provide real-time traffic data, video streams, incidents, and enforcement events to Integrated Command and Control Centers (ICCCs).
This integration enables centralized monitoring, cross-department coordination, and city-wide situational awareness, allowing traffic operations to become part of unified Smart City governance rather than isolated systems.

Smart City traffic projects usually consist of multiple integrated subsystems operating on a common platform.
These typically include traffic monitoring and control systems, automated traffic enforcement, video-based incident detection, traffic survey and data collection systems, traveler information systems, and integration with ICCCs and emergency services.
Together, these subsystems support daily operations, safety enforcement, and long-term urban mobility planning.

A Traffic Management System focuses on real-time monitoring and operational control of traffic, including congestion management, signal coordination, and incident response.
An Intelligent Transportation System (ITS) is a broader framework that integrates traffic management with enforcement systems, data analytics, communication networks, and decision support platforms.
In practice, traffic management is a core operational component within an ITS architecture, while ITS enables data-driven, predictive, and policy-oriented mobility governance.

Traffic Pulse – Survey Intelligence supports the most commonly required traffic survey types used in professional traffic engineering and planning projects, including:

• Automatic Traffic Count and Classification (ATCC)

• Turning Movement Counts (TMC)

• Classified Volume Counts (CVC)

• Speed and directional studies

• Pedestrian and mixed-traffic surveys

The platform is designed to adapt to survey objectives rather than enforcing a rigid survey format.

Accuracy is ensured through a system-level approach that combines:

• Video-based source data instead of real-time manual observation

• AI-based vehicle detection, tracking, and classification

• Consistent analytics logic across locations and survey days

• Video-to-data traceability for validation and audit

• Automated data processing and structured reporting

This ensures accuracy that is both technically reliable and demonstrable during review.

Yes. All traffic data generated by the platform is directly traceable to the source traffic video.
Surveyors, consultants, and reviewers can validate counts and classifications by referring back to the video footage with timeline, making the data suitable for technical review, dispute resolution, and audits.

Survey outputs are available in multiple formats to support different project needs, including:

• Structured survey reports for documentation and DPRs

• Tabular datasets for analysis and traffic modeling

• Charts and visual summaries for presentations and reviews

All outputs are organized by survey location, date, and type for easy access and reuse.

Yes. Traffic Pulse – Survey Intelligence is designed to manage large and complex survey programs.
It can handle multiple locations, directions, and survey days within a single project while maintaining consistent data structure and analysis logic across all outputs.

The platform reduces survey costs by:

• Eliminating manual traffic counting

• Reducing manpower and supervision requirements

• Automating data processing and report generation

• Minimizing re-surveys caused by data disputes

• Scaling surveys without proportional cost increases

This results in lower total survey cost and improved return on investment.

Yes. Traffic Pulse – Survey Intelligence is suitable for government and regulatory use.
It produces structured, validation-ready outputs that support DPR preparation, technical scrutiny, and compliance reviews, aligning well with institutional and authority requirements.

Yes. The platform is well suited for Smart City, Highways and large infrastructure projects that require:

• Standardized survey execution

• Consistent outputs across multiple stakeholders

• Scalable handling of large survey footprints

It supports coordinated, data-driven decision-making across Smart City traffic and Highways initiatives.

Yes. The platform can process long-duration traffic videos and extended survey periods without increasing manual effort, making it suitable for continuous, peak-hour, or time-intensive traffic studies.

Traffic survey results are available significantly faster than traditional manual methods.
Once videos are uploaded, automated analysis generates structured data, charts, and reports with minimal turnaround time, depending on survey volume and duration.